Collect Atlassian Confluence logs

Supported in:

Google secops SIEM

This document explains how to ingest Atlassian Confluence logs to Google Security Operations. The parser first attempts to extract fields from the raw log message using regular expressions (grok patterns) designed for Atlassian Confluence logs. If the grok parsing fails or the log is in JSON format, the code then attempts to parse the message as JSON. Finally, the extracted fields are mapped to the Google SecOps UDM schema and enriched with additional context.

Before you begin

Make sure you have the following prerequisites:

A Google SecOps instance
An Atlassian Confluence Cloud account with audit log access OR Confluence Data Center/Server with administrative access
For GCP-based method: Privileged access to GCP (GCS, IAM, Cloud Run, Pub/Sub, Cloud Scheduler)
For Bindplane method: Windows Server 2016 or later, or Linux host with systemd

Integration options overview

This guide provides two integration paths:

Option 1: Confluence Data Center/Server via Bindplane + Syslog
Option 2: Confluence Cloud Audit Logs via GCP Cloud Run function + GCS (JSON format)

Choose the option that best fits your Confluence deployment type and infrastructure.

Option 1: Confluence Data Center/Server via Bindplane + Syslog

This option configures Confluence Data Center or Server to send logs via syslog to a Bindplane agent, which then forwards them to Google SecOps.

Get Google SecOps ingestion authentication file

Sign in to the Google SecOps console.
Go to SIEM Settings > Collection Agents.
Click Download to download the ingestion authentication file.
Save the file securely on the system where Bindplane agent will be installed.

Note: This JSON file contains credentials for authenticating the Bindplane agent to Google SecOps.

Get Google SecOps customer ID

Sign in to the Google SecOps console.
Go to SIEM Settings > Profile.
Copy and save the Customer ID from the Organization Details section.

Note: The customer ID is required for configuring the Bindplane agent exporter.

Install Bindplane agent

Install the Bindplane agent on your Windows or Linux operating system according to the following instructions.

Windows installation

Open Command Prompt or PowerShell as an administrator.

Run the following command:

msiexec /i "https://github.com/observIQ/bindplane-otel-collector/releases/latest/download/observiq-otel-collector.msi" /quiet

Wait for the installation to complete.
Verify the installation by running:
```
sc query observiq-otel-collector
```

The service should show as RUNNING.

Linux installation

Open a terminal with root or sudo privileges.

Run the following command:

sudo sh -c "$(curl -fsSlL https://github.com/observIQ/bindplane-otel-collector/releases/latest/download/install_unix.sh)" install_unix.sh

Wait for the installation to complete.

Verify the installation by running:

sudo systemctl status observiq-otel-collector

The service should show as active (running).

Additional installation resources

For additional installation options and troubleshooting, see Bindplane agent installation guide.

Configure Bindplane agent to ingest syslog and send to Google SecOps

Locate the configuration file

Linux:

sudo nano /etc/bindplane-agent/config.yaml

Windows:

notepad "C:\Program Files\observIQ OpenTelemetry Collector\config.yaml"

Edit the configuration file

Replace the entire contents of config.yaml with the following configuration:

receivers:
  udplog:
    listen_address: "0.0.0.0:514"

exporters:
  chronicle/confluence_logs:
    compression: gzip
    creds_file_path: '/etc/bindplane-agent/ingestion-auth.json'
    customer_id: 'YOUR_CUSTOMER_ID'
    endpoint: malachiteingestion-pa.googleapis.com
    log_type: ATLASSIAN_CONFLUENCE
    raw_log_field: body
    ingestion_labels:
      service: confluence

service:
  pipelines:
    logs/confluence:
      receivers:
        - udplog
      exporters:
        - chronicle/confluence_logs

Configuration parameters

Replace the following placeholders:
- listen_address: Replace the port and IP address as required in your infrastructure. Use 0.0.0.0:514 to listen on all interfaces on port 514.
- creds_file_path: Update to the path where the authentication file was saved:
  - Linux: /etc/bindplane-agent/ingestion-auth.json
  - Windows: C:\Program Files\observIQ OpenTelemetry Collector\ingestion-auth.json
- customer_id: Replace YOUR_CUSTOMER_ID with the actual customer ID from the previous step.
- endpoint: Regional endpoint URL:
  - US: malachiteingestion-pa.googleapis.com
  - Europe: europe-malachiteingestion-pa.googleapis.com
  - Asia: asia-southeast1-malachiteingestion-pa.googleapis.com

Save the configuration file

After editing, save the file:

Linux: Press Ctrl+O, then Enter, then Ctrl+X
Windows: Click File > Save

Restart the Bindplane agent to apply the changes

Restart the Bindplane agent in Linux

To restart the Bindplane agent in Linux, run the following command:
```
sudo systemctl restart observiq-otel-collector
```

Verify the service is running:

sudo systemctl status observiq-otel-collector

Check logs for errors:

sudo journalctl -u observiq-otel-collector -f

Restart the Bindplane agent in Windows

To restart the Bindplane agent in Windows, choose one of the following options:
- Using Command Prompt or PowerShell as administrator:
```
net stop observiq-otel-collector && net start observiq-otel-collector
```
- Using Services console:
  1. Press Win+R, type services.msc, and press Enter.
  2. Locate observIQ OpenTelemetry Collector.
  3. Right-click and select Restart.
  4. Verify the service is running:
```
sc query observiq-otel-collector
```
  5. Check logs for errors:
```
type "C:\Program Files\observIQ OpenTelemetry Collector\log\collector.log"
```

Configure Syslog forwarding on Confluence Data Center/Server

Option A: Configure rsyslog to forward local log files (Recommended)

Configure Confluence to write logs to files (default behavior).

Install rsyslog if not present:

sudo apt-get install rsyslog  # Debian/Ubuntu
sudo yum install rsyslog      # RHEL/CentOS

Create rsyslog configuration file /etc/rsyslog.d/confluence.conf:

# Forward Confluence logs to Bindplane
$ModLoad imfile

# Application logs
$InputFileName /opt/atlassian/confluence/logs/atlassian-confluence.log
$InputFileTag confluence-app:
$InputFileStateFile stat-confluence-app
$InputFileSeverity info
$InputFileFacility local0
$InputRunFileMonitor

# Audit logs (JSON format in DC/Server)
$InputFileName <confluence-home-directory>/log/audit/audit.log
$InputFileTag confluence-audit:
$InputFileStateFile stat-confluence-audit
$InputFileSeverity info
$InputFileFacility local1
$InputRunFileMonitor

# Forward to Bindplane agent
*.* @@BINDPLANE_AGENT_IP:514

Replace BINDPLANE_AGENT_IP with the IP address of the Bindplane agent (for example, 192.168.1.100).
Adjust log file paths based on your Confluence installation:
- Application logs typically: <confluence-install>/logs/ or <local-home>/logs/
- Audit logs: <confluence-home-directory>/log/audit/ (JSON format)
- To find your Confluence home directory, go to Settings > General Configuration > System Information and look for Confluence Home or Local Home.

Restart rsyslog:
```
sudo systemctl restart rsyslog
```

Option B: Configure Log4j2 Syslog forwarding

This option requires modifying Log4j2 configuration. Option A (rsyslog) is recommended for simplicity.

Sign in to your Confluence server via SSH or RDP.
Locate the Log4j2 configuration file at:
```
<confluence-install>/confluence/WEB-INF/classes/log4j2.xml
```
Note: Adjust path based on your Confluence installation.

Edit the configuration file to add a Syslog appender:

<Configuration>
  <Appenders>
    <!-- Existing appenders -->
    <Syslog name="SyslogAppender" 
            host="BINDPLANE_AGENT_IP" 
            port="514" 
            protocol="UDP"
            format="RFC5424"
            facility="LOCAL0">
      <PatternLayout pattern="%d{ISO8601} %p [%t] [%c{1}] %m%n"/>
    </Syslog>
  </Appenders>

  <Loggers>
    <Root level="info">
      <AppenderRef ref="SyslogAppender"/>
      <!-- Other appender refs -->
    </Root>

    <!-- Audit logger -->
    <Logger name="com.atlassian.confluence.event.events.security.AuditEvent" 
            level="info" 
            additivity="false">
      <AppenderRef ref="SyslogAppender"/>
    </Logger>
  </Loggers>
</Configuration>

Replace BINDPLANE_AGENT_IP with the IP address of the Bindplane agent (for example, 192.168.1.100).

Restart Confluence to apply changes:
```
sudo systemctl restart confluence
```

Option 2: Confluence Cloud Audit Logs via GCP Cloud Run function and GCS

This method uses GCP Cloud Run function to periodically fetch audit logs via the Confluence Audit REST API and store them in GCS for Google SecOps ingestion.

Collect Confluence Cloud API credentials

Sign in to your Atlassian account.
Go to https://id.atlassian.com/manage-profile/security/api-tokens.
Click Create API token.
Enter a label for the token (for example, Google Security Operations Integration).
Click Create.
Copy and save the API token securely.
Note your Confluence Cloud site URL (for example, https://yoursite.atlassian.net).
Note your Atlassian account email address (used for authentication).

Note: The API token requires 'Confluence Administrator' global permission to access audit logs.

Verify permissions

To verify the account has the required permissions:

Sign in to Confluence Cloud.
Click the Settings icon (⚙️) in the top-right corner.
If you can see Monitoring > Audit log in the left-hand navigation, you have the required permissions.
If you cannot see this option, contact your administrator to grant Confluence Administrator permission.

Test API access

Test your credentials before proceeding with the integration:

# Replace with your actual credentials
CONFLUENCE_EMAIL="your-email@example.com"
CONFLUENCE_API_TOKEN="your-api-token"
CONFLUENCE_URL="https://yoursite.atlassian.net"

# Test API access
curl -u "${CONFLUENCE_EMAIL}:${CONFLUENCE_API_TOKEN}" \
  -H "Accept: application/json" \
  "${CONFLUENCE_URL}/wiki/rest/api/audit"

Create Google Cloud Storage bucket

Go to the Google Cloud Console.
Select your project or create a new one.
In the navigation menu, go to Cloud Storage > Buckets.
Click Create bucket.

Provide the following configuration details:

Setting	Value
Name your bucket	Enter a globally unique name (for example, `confluence-audit-logs`)
Location type	Choose based on your needs (Region, Dual-region, Multi-region)
Location	Select the location (for example, `us-central1`)
Storage class	Standard (recommended for frequently accessed logs)
Access control	Uniform (recommended)
Protection tools	Optional: Enable object versioning or retention policy

Click Create.

Create service account for Cloud Run function

The Cloud Run function needs a service account with permissions to write to GCS bucket and be invoked by Pub/Sub.

Create service account

In the GCP Console, go to IAM & Admin > Service Accounts.
Click Create Service Account.
Provide the following configuration details:
- Service account name: Enter confluence-audit-collector-sa.
- Service account description: Enter Service account for Cloud Run function to collect Confluence Cloud audit logs.
Click Create and Continue.
In the Grant this service account access to project section, add the following roles:
1. Click Select a role.
2. Search for and select Storage Object Admin.
3. Click + Add another role.
4. Search for and select Cloud Run Invoker.
5. Click + Add another role.
6. Search for and select Cloud Functions Invoker.
Click Continue.
Click Done.

These roles are required for:

Storage Object Admin: Write logs to GCS bucket and manage state files
Cloud Run Invoker: Allow Pub/Sub to invoke the function
Cloud Functions Invoker: Allow function invocation

Grant IAM permissions on GCS bucket

Grant the service account write permissions on the GCS bucket:

Go to Cloud Storage > Buckets.
Click your bucket name.
Go to the Permissions tab.
Click Grant access.
Provide the following configuration details:
- Add principals: Enter the service account email (for example, confluence-audit-collector-sa@PROJECT_ID.iam.gserviceaccount.com).
- Assign roles: Select Storage Object Admin.
Click Save.

Create Pub/Sub topic

Create a Pub/Sub topic that Cloud Scheduler will publish to and the Cloud Run function will subscribe to.

In the GCP Console, go to Pub/Sub > Topics.
Click Create topic.
Provide the following configuration details:
- Topic ID: Enter confluence-audit-trigger.
- Leave other settings as default.
Click Create.

Create Cloud Run function to collect logs

The Cloud Run function is triggered by Pub/Sub messages from Cloud Scheduler to fetch logs from Confluence Cloud Audit API and writes them to GCS.

In the GCP Console, go to Cloud Run.
Click Create service.
Select Function (use an inline editor to create a function).
In the Configure section, provide the following configuration details:

Setting Value

Service name confluence-audit-collector

Region Select region matching your GCS bucket (for example, us-central1)

Runtime Select Python 3.12 or later
In the Trigger (optional) section:
1. Click + Add trigger.
2. Select Cloud Pub/Sub.
3. In Select a Cloud Pub/Sub topic, choose confluence-audit-trigger.
4. Click Save.
In the Authentication section:
1. Select Require authentication.
2. Check Identity and Access Management (IAM).
Note: Pub/Sub will automatically handle authentication when invoking the function.
Scroll down and expand Containers, Networking, Security.
Go to the Security tab:
- Service account: Select confluence-audit-collector-sa.

Setting	Value
Service name	`confluence-audit-collector`
Region	Select region matching your GCS bucket (for example, `us-central1`)
Runtime	Select Python 3.12 or later

Go to the Containers tab:

Click Variables & Secrets.
Click + Add variable for each environment variable:

Variable Name	Example Value	Description
`GCS_BUCKET`	`confluence-audit-logs`	GCS bucket name
`GCS_PREFIX`	`confluence-audit`	Prefix for log files
`STATE_KEY`	`confluence-audit/state.json`	State file path
`CONFLUENCE_URL`	`https://yoursite.atlassian.net`	Confluence site URL
`CONFLUENCE_EMAIL`	`your-email@example.com`	Atlassian account email
`CONFLUENCE_API_TOKEN`	`your-api-token-here`	API token
`MAX_RECORDS`	`1000`	Max records per run

In the Variables & Secrets section, scroll down to Requests:
- Request timeout: Enter 600 seconds (10 minutes).
Go to the Settings tab:
- In the Resources section:
  - Memory: Select 512 MiB or higher.
  - CPU: Select 1.
In the Revision scaling section:
- Minimum number of instances: Enter 0.
- Maximum number of instances: Enter 100 (or adjust based on expected load).
Click Create.
Wait for the service to be created (1-2 minutes).
After the service is created, the inline code editor opens automatically.

Add function code

Enter main in Function entry point

In the inline code editor, create two files:

First file: main.py:

import functions_framework
from google.cloud import storage
import json
import os
import urllib3
from datetime import datetime, timezone, timedelta
import time
import base64

# Initialize HTTP client with timeouts
http = urllib3.PoolManager(
    timeout=urllib3.Timeout(connect=5.0, read=30.0),
    retries=False,
)

# Initialize Storage client
storage_client = storage.Client()

# Environment variables
GCS_BUCKET = os.environ.get('GCS_BUCKET')
GCS_PREFIX = os.environ.get('GCS_PREFIX', 'confluence-audit/')
STATE_KEY = os.environ.get('STATE_KEY', 'confluence-audit/state.json')
CONFLUENCE_URL = os.environ.get('CONFLUENCE_URL')
CONFLUENCE_EMAIL = os.environ.get('CONFLUENCE_EMAIL')
CONFLUENCE_API_TOKEN = os.environ.get('CONFLUENCE_API_TOKEN')
MAX_RECORDS = int(os.environ.get('MAX_RECORDS', '1000'))

def to_unix_millis(dt: datetime) -> int:
    """Convert datetime to Unix epoch milliseconds."""
    if dt.tzinfo is None:
        dt = dt.replace(tzinfo=timezone.utc)
    dt = dt.astimezone(timezone.utc)
    return int(dt.timestamp() * 1000)

def parse_datetime(value: str) -> datetime:
    """Parse ISO datetime string to datetime object."""
    if value.endswith("Z"):
        value = value[:-1] + "+00:00"
    return datetime.fromisoformat(value)

@functions_framework.cloud_event
def main(cloud_event):
    """
    Cloud Run function triggered by Pub/Sub to fetch Confluence Cloud audit logs and write to GCS.

    Args:
        cloud_event: CloudEvent object containing Pub/Sub message
    """

    if not all([GCS_BUCKET, CONFLUENCE_URL, CONFLUENCE_EMAIL, CONFLUENCE_API_TOKEN]):
        print('Error: Missing required environment variables')
        return

    try:
        # Get GCS bucket
        bucket = storage_client.bucket(GCS_BUCKET)

        # Load state
        state = load_state(bucket, STATE_KEY)

        # Determine time window
        now = datetime.now(timezone.utc)
        last_time = None

        if isinstance(state, dict) and state.get("last_event_time"):
            try:
                last_time = parse_datetime(state["last_event_time"])
                # Overlap by 2 minutes to catch any delayed events
                last_time = last_time - timedelta(minutes=2)
            except Exception as e:
                print(f"Warning: Could not parse last_event_time: {e}")

        if last_time is None:
            last_time = now - timedelta(hours=24)

        print(f"Fetching logs from {last_time.isoformat()} to {now.isoformat()}")

        # Convert to Unix milliseconds
        start_millis = to_unix_millis(last_time)
        end_millis = to_unix_millis(now)

        # Fetch logs
        records, newest_event_time = fetch_logs(
            api_base=CONFLUENCE_URL,
            email=CONFLUENCE_EMAIL,
            api_token=CONFLUENCE_API_TOKEN,
            start_time_ms=start_millis,
            end_time_ms=end_millis,
            max_records=MAX_RECORDS,
        )

        if not records:
            print("No new log records found.")
            save_state(bucket, STATE_KEY, now.isoformat())
            return

        # Write to GCS as NDJSON
        timestamp = now.strftime('%Y%m%d_%H%M%S')
        object_key = f"{GCS_PREFIX}/logs_{timestamp}.ndjson"
        blob = bucket.blob(object_key)

        ndjson = '\n'.join([json.dumps(record, ensure_ascii=False) for record in records]) + '\n'
        blob.upload_from_string(ndjson, content_type='application/x-ndjson')

        print(f"Wrote {len(records)} records to gs://{GCS_BUCKET}/{object_key}")

        # Update state with newest event time
        if newest_event_time:
            save_state(bucket, STATE_KEY, newest_event_time)
        else:
            save_state(bucket, STATE_KEY, now.isoformat())

        print(f"Successfully processed {len(records)} records")

    except Exception as e:
        print(f'Error processing logs: {str(e)}')
        raise

def load_state(bucket, key):
    """Load state from GCS."""
    try:
        blob = bucket.blob(key)
        if blob.exists():
            state_data = blob.download_as_text()
            return json.loads(state_data)
    except Exception as e:
        print(f"Warning: Could not load state: {e}")

    return {}

def save_state(bucket, key, last_event_time_iso: str):
    """Save the last event timestamp to GCS state file."""
    try:
        state = {'last_event_time': last_event_time_iso}
        blob = bucket.blob(key)
        blob.upload_from_string(
            json.dumps(state, indent=2),
            content_type='application/json'
        )
        print(f"Saved state: last_event_time={last_event_time_iso}")
    except Exception as e:
        print(f"Warning: Could not save state: {e}")

def fetch_logs(api_base: str, email: str, api_token: str, start_time_ms: int, end_time_ms: int, max_records: int):
    """
    Fetch logs from Confluence Cloud Audit API with pagination and rate limiting.

    Args:
        api_base: Confluence site URL
        email: Atlassian account email
        api_token: API token
        start_time_ms: Start time in Unix milliseconds
        end_time_ms: End time in Unix milliseconds
        max_records: Maximum total records to fetch

    Returns:
        Tuple of (records list, newest_event_time ISO string)
    """
    # Clean up URL
    base_url = api_base.rstrip('/')

    # Build authentication header
    auth_string = f"{email}:{api_token}"
    auth_bytes = auth_string.encode('utf-8')
    auth_b64 = base64.b64encode(auth_bytes).decode('utf-8')
    headers = {
        'Authorization': f'Basic {auth_b64}',
        'Accept': 'application/json',
        'User-Agent': 'GoogleSecOps-ConfluenceCollector/1.0'
    }

    records = []
    newest_time = None
    page_num = 0
    backoff = 1.0
    start_index = 0

    while True:
        page_num += 1

        if len(records) >= max_records:
            print(f"Reached max_records limit ({max_records})")
            break

        # Build request URL
        url = f"{base_url}/wiki/rest/api/audit?startDate={start_time_ms}&endDate={end_time_ms}&start={start_index}&limit=100"

        try:
            response = http.request('GET', url, headers=headers)

            # Handle rate limiting with exponential backoff
            if response.status == 429:
                retry_after = int(response.headers.get('Retry-After', str(int(backoff))))
                print(f"Rate limited (429). Retrying after {retry_after}s...")
                time.sleep(retry_after)
                backoff = min(backoff * 2, 30.0)
                continue

            backoff = 1.0

            if response.status != 200:
                print(f"HTTP Error: {response.status}")
                response_text = response.data.decode('utf-8')
                print(f"Response body: {response_text}")
                return [], None

            data = json.loads(response.data.decode('utf-8'))

            page_results = data.get('results', [])

            if not page_results:
                print(f"No more results (empty page)")
                break

            print(f"Page {page_num}: Retrieved {len(page_results)} events")
            records.extend(page_results)

            # Track newest event time
            for event in page_results:
                try:
                    # creationDate is in Unix milliseconds
                    event_time_ms = event.get('creationDate')
                    if event_time_ms:
                        event_dt = datetime.fromtimestamp(event_time_ms / 1000, tz=timezone.utc)
                        event_time = event_dt.isoformat()
                        if newest_time is None or parse_datetime(event_time) > parse_datetime(newest_time):
                            newest_time = event_time
                except Exception as e:
                    print(f"Warning: Could not parse event time: {e}")

            # Check for more results
            current_size = data.get('size', 0)
            if current_size < 100:
                print(f"Reached last page (size={current_size} < limit=100)")
                break

            start_index += current_size

        except Exception as e:
            print(f"Error fetching logs: {e}")
            return [], None

    print(f"Retrieved {len(records)} total records from {page_num} pages")
    return records[:max_records], newest_time

Second file: requirements.txt:

functions-framework==3.*
google-cloud-storage==2.*
urllib3>=2.0.0

Click Deploy to save and deploy the function.
Wait for deployment to complete (2-3 minutes).

Note: The Pub/Sub trigger configuration automatically creates the necessary subscriptions and permissions.

Create Cloud Scheduler job

Cloud Scheduler publishes messages to the Pub/Sub topic at regular intervals, triggering the Cloud Run function.

In the GCP Console, go to Cloud Scheduler.
Click Create Job.

Provide the following configuration details:

Setting	Value
Name	`confluence-audit-collector-hourly`
Region	Select same region as Cloud Run function
Frequency	`0 * * * *` (every hour, on the hour)
Timezone	Select timezone (UTC recommended)
Target type	Pub/Sub
Topic	Select `confluence-audit-trigger`
Message body	`{}` (empty JSON object)

Click Create.

Schedule frequency options

Choose frequency based on log volume and latency requirements:

Frequency	Cron Expression	Use Case
Every 5 minutes	`/5 * * *`	High-volume, low-latency
Every 15 minutes	`/15 * * *`	Medium volume
Every hour	`0 * * * *`	Standard (recommended)
Every 6 hours	`0 /6 * *`	Low volume, batch processing
Daily	`0 0 * * *`	Historical data collection

Test the integration

In the Cloud Scheduler console, find your job.
Click Force run to trigger the job manually.
Wait a few seconds.
Go to Cloud Run > Services.
Click on confluence-audit-collector.
Click the Logs tab.

Verify the function executed successfully. Look for the following:

Fetching logs from YYYY-MM-DDTHH:MM:SS+00:00 to YYYY-MM-DDTHH:MM:SS+00:00
Page 1: Retrieved X events
Wrote X records to gs://bucket-name/prefix/logs_YYYYMMDD_HHMMSS.ndjson
Successfully processed X records

Go to Cloud Storage > Buckets.
Click your bucket name.
Navigate to the confluence-audit/ folder.
Verify that a new .ndjson file was created with the current timestamp.

If you see errors in the logs:

HTTP 401: Check API credentials in environment variables
HTTP 403: Verify account has Confluence Administrator permissions
HTTP 429: Rate limiting - function will automatically retry with backoff
Missing environment variables: Check all required variables are set

Retrieve the Google SecOps service account

Google SecOps uses a unique service account to read data from your GCS bucket. You must grant this service account access to your bucket.

Get the service account email

Go to SIEM Settings > Feeds.
Click Add New Feed.
Click Configure a single feed.
In the Feed name field, enter a name for the feed (for example, Confluence Cloud Audit Logs).
Select Google Cloud Storage V2 as the Source type.
Select Atlassian Confluence as the Log type.
Click Get Service Account. A unique service account email will be displayed, for example:
```
chronicle-12345678@chronicle-gcp-prod.iam.gserviceaccount.com
```
Copy this email address for use in the next step.

Note: Each Google SecOps instance has a unique service account. Do not use service accounts from other documentation or examples.

Grant IAM permissions to the Google SecOps service account

The Google SecOps service account needs Storage Object Viewer role on your GCS bucket.

Go to Cloud Storage > Buckets.
Click your bucket name.
Go to the Permissions tab.
Click Grant access.
Provide the following configuration details:
- Add principals: Paste the Google SecOps service account email.
- Assign roles: Select Storage Object Viewer.
Click Save.

Note: If you plan to use the deletion option "Delete transferred files" or "Delete transferred files and empty directories," grant Storage Object Admin role instead of Storage Object Viewer.

Configure a feed in Google SecOps to ingest Confluence logs

Go to SIEM Settings > Feeds.
Click Add New Feed.
Click Configure a single feed.
In the Feed name field, enter a name for the feed (for example, Confluence Cloud Audit Logs).
Select Google Cloud Storage V2 as the Source type.
Select Atlassian Confluence as the Log type.
Click Next.
Specify values for the following input parameters:
- Storage bucket URL: Enter the GCS bucket URI with the prefix path:
```
gs://confluence-audit-logs/confluence-audit/
```
  - Replace:
    - confluence-audit-logs: Your GCS bucket name.
    - confluence-audit: Optional prefix/folder path where logs are stored (leave empty for root).
  - Examples:
    - Root bucket: gs://company-logs/
    - With prefix: gs://company-logs/confluence-audit/
    - With subfolder: gs://company-logs/confluence/audit/
  Note: Always include the trailing slash (/) at the end of the URI.
- Source deletion option: Select the deletion option according to your preference:
  - Never: Never deletes any files after transfers (recommended for testing).
  - Delete transferred files: Deletes files after successful transfer.
  - Delete transferred files and empty directories: Deletes files and empty directories after successful transfer.
    
    Note: If you select a deletion option, the service account must have Storage Object Admin role instead of Storage Object Viewer. Update IAM permissions accordingly.
- Maximum File Age: Include files modified in the last number of days. Default is 180 days.
- Asset namespace: The asset namespace.
- Ingestion labels: The label to be applied to the events from this feed.
Click Next.
Review your new feed configuration in the Finalize screen, and then click Submit.

UDM mapping table

Log Field	UDM Mapping	Logic
agent	read_only_udm.network.http.user_agent	Value taken from "agent" field.
app_protocol	read_only_udm.network.application_protocol	Derived from "app_protocol" field. If "app_protocol" contains "HTTPS", "HTTP", "SSH", or "RDP", the corresponding protocol is used. Otherwise, it defaults to "UNKNOWN_APPLICATION_PROTOCOL".
app_protocol	read_only_udm.network.application_protocol_version	Value taken from "app_protocol" field.
auditType.action	read_only_udm.security_result.action	Derived from "auditType.action" field. If "auditType.action" contains "successful", the value is set to "ALLOW". If it contains "restricted", the value is set to "BLOCK".
auditType.action	read_only_udm.security_result.summary	Value taken from "auditType.action" field when "auditType" is not empty and "auditType_area" is "SECURITY".
auditType.actionI18nKey	read_only_udm.metadata.product_event_type	Value taken from "auditType.actionI18nKey" field when "auditType" is not empty.
auditType.area	read_only_udm.security_result.detection_fields.value	Value taken from "auditType.area" field and assigned to the "value" field of a detection field with the "key" field set to "auditType area". This mapping is done when "auditType" is not empty.
auditType.category	read_only_udm.security_result.category_details	Value taken from "auditType.category" field when "auditType" is not empty.
auditType.categoryI18nKey	read_only_udm.security_result.detection_fields.value	Value taken from "auditType.categoryI18nKey" field and assigned to the "value" field of a detection field with the "key" field set to "auditType categoryI18nKey". This mapping is done when "auditType" is not empty.
auditType.level	read_only_udm.security_result.detection_fields.value	Value taken from "auditType.level" field and assigned to the "value" field of a detection field with the "key" field set to "auditType level". This mapping is done when "auditType" is not empty.
author.displayName	read_only_udm.principal.user.user_display_name	Value taken from "author.displayName" field.
author.externalCollaborator	read_only_udm.security_result.about.resource.attribute.labels.value	Value taken from "author.externalCollaborator" field and assigned to the "value" field of a label with the "key" field set to "externalCollaborator".
author.id	read_only_udm.principal.user.userid	Value taken from "author.id" field when "author.type" is "user" and "principal_user_present" is "false".
author.isExternalCollaborator	read_only_udm.security_result.about.resource.attribute.labels.value	Value taken from "author.isExternalCollaborator" field and assigned to the "value" field of a label with the "key" field set to "isExternalCollaborator".
author.name	read_only_udm.principal.user.user_display_name	Value taken from "author.name" field when "author.type" is "user" and "principal_user_present" is "false".
bytes_in	read_only_udm.network.received_bytes	Value taken from "bytes_in" field if it contains digits. Otherwise, it defaults to 0.
category	read_only_udm.security_result.category_details	Value taken from "category" field.
changedValues	read_only_udm.principal.resource.attribute.labels	Iterates through each element in "changedValues" and creates labels with keys like "changedValue [index] [key]" and values from the corresponding values in the "changedValues" array.
creationDate	read_only_udm.metadata.event_timestamp	Value taken from "creationDate" field, parsed as either UNIX or UNIX_MS timestamp.
extraAttributes	read_only_udm.principal.resource.attribute.labels	Iterates through each element in "extraAttributes" and creates labels with keys based on "name" and "nameI18nKey" fields and values from the corresponding "value" field.
http_verb	read_only_udm.network.http.method	Value taken from "http_verb" field.
ip	read_only_udm.target.ip	Value taken from "ip" field.
principal_host	read_only_udm.principal.hostname	Value taken from "principal_host" field.
referral_url	read_only_udm.network.http.referral_url	Value taken from "referral_url" field.
remoteAddress	read_only_udm.principal.ip	Value taken from "remoteAddress" field, parsed as an IP address.
response_code	read_only_udm.network.http.response_code	Value taken from "response_code" field.
session_duration	read_only_udm.additional.fields.value.string_value	Value taken from "session_duration" field and assigned to the "string_value" field of a label with the "key" field set to "Session Duration".
source	read_only_udm.principal.ip	Value taken from "source" field, parsed as an IP address.
src_ip	read_only_udm.principal.ip	Value taken from "src_ip" field if "remoteAddress" is empty.
summary	read_only_udm.security_result.summary	Value taken from "summary" field.
sysAdmin	read_only_udm.security_result.about.resource.attribute.labels.value	Value taken from "sysAdmin" field and assigned to the "value" field of a label with the "key" field set to "sysAdmin".
superAdmin	read_only_udm.security_result.about.resource.attribute.labels.value	Value taken from "superAdmin" field and assigned to the "value" field of a label with the "key" field set to "superAdmin".
target_url	read_only_udm.target.url	Value taken from "target_url" field.
timestamp	read_only_udm.metadata.event_timestamp	Value taken from "timestamp" field, parsed as a date and time string.
user_id	read_only_udm.principal.user.userid	Value taken from "user_id" field.
	read_only_udm.metadata.event_type	This field's value is determined by a series of checks and defaults to "GENERIC_EVENT". It is set to specific values like "NETWORK_HTTP", "USER_UNCATEGORIZED", or "STATUS_UPDATE" based on the presence and content of other fields like "principal_host", "user_id", "has_principal", and "author.type".
	read_only_udm.metadata.vendor_name	Set to "ATLASSIAN".
	read_only_udm.metadata.product_name	Set to "CONFLUENCE".
	read_only_udm.metadata.log_type	Set to "ATLASSIAN_CONFLUENCE".
	read_only_udm.principal.user.user_display_name	This field's value can come from either "author.displayName" or "affectedObject.name" depending on the context.
	read_only_udm.target.process.pid	This field's value can come from either "principal_host" or "pid" depending on the context.
	read_only_udm.principal.resource.attribute.labels	This field is populated with various labels derived from fields like "affectedObjects", "changedValues", and "extraAttributes". The keys and values of these labels are dynamically generated based on the specific content of these fields.

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